yhuai
24 May 2018
This is an R Markdown presentation. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document.
Create a web page presentation using R Markdown that features a plot created with Plotly. Host your webpage on either GitHub Pages, RPubs, or NeoCities. Your webpage must contain the date that you created the document, and it must contain a plot created with Plotly. We would love to see you show off your creativity!
library(plotly)
datasets::mtcars mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2plot_ly(mtcars, x = mtcars$wt, y=mtcars$mpg, mode = "markers")plot_ly(mtcars, x = mtcars$wt, y=mtcars$mpg, mode = "markers", color = as.factor(mtcars$cyl))plot_ly(mtcars, x = mtcars$wt, y=mtcars$mpg, mode = "markers", color = mtcars$disp)plot_ly(mtcars, x = mtcars$wt, y=mtcars$mpg, mode = "markers", color = as.factor(mtcars$cyl),size=mtcars$hp)library(plotly)
set.seed(1993)
temp <- rnorm(100, mean=30, sd=5)
pressue <- rnorm(100)
dtime <- 1:100
plot_ly(x = temp, y = pressue, z = dtime,
type = "scatter3d", mode="markers", color=temp)data("airmiles")
airmilesTime Series:
Start = 1937
End = 1960
Frequency = 1
[1] 412 480 683 1052 1385 1418 1634 2178 3362 5948 6109
[12] 5981 6753 8003 10566 12528 14760 16769 19819 22362 25340 25343
[23] 29269 30514plot_ly(x=time(airmiles), y=airmiles)library(plotly);library(tidyr);library(dplyr)
data("EuStockMarkets")
stocks <- as.data.frame(EuStockMarkets) %>%
gather(index,price) %>%
mutate(time=rep(time(EuStockMarkets),4))
plot_ly(stocks, x = stocks$time, y = stocks$price, color=stocks$index)plot_ly(iris, x = iris$Petal.Length, type="histogram" )plot_ly(iris, y = iris$Petal.Length, color = iris$Species, type="box" )terrain1 <- matrix(rnorm(100*100), nrow = 100, ncol=100)
plot_ly(z=terrain1, type="heatmap")terrain2 <- matrix(sort(rnorm(100*100)), nrow = 100, ncol=100)
plot_ly(z=terrain2, type="surface")